Daily Arxiv

전 세계에서 발간되는 인공지능 관련 논문을 정리하는 페이지 입니다.
본 페이지는 Google Gemini를 활용해 요약 정리하며, 비영리로 운영 됩니다.
논문에 대한 저작권은 저자 및 해당 기관에 있으며, 공유 시 출처만 명기하면 됩니다.

OmniEVA: Embodied Versatile Planner via Task-Adaptive 3D-Grounded and Embodiment-aware Reasoning

Open-sci-ref-0.01: open and reproducible reference baselines for language model and dataset comparison

Similarity-based Outlier Detection for Noisy Object Re-Identification Using Beta Mixtures

MachineLearningLM: Scaling Many-shot In-context Learning via Continued Pretraining

Musculoskeletal simulation of limb movement biomechanics in Drosophila melanogaster

Between a Rock and a Hard Place: Exploiting Ethical Reasoning to Jailbreak LLMs

Cut Costs, Not Accuracy: LLM-Powered Data Processing with Guarantees

The Architecture of AI Transformation: Four Strategic Patterns and an Emerging Frontier

IS${}^3$ : Generic Impulsive--Stationary Sound Separation in Acoustic Scenes using Deep Filtering

Beyond Ensembles: Simulating All-Atom Protein Dynamics in a Learned Latent Space

HiddenObject: Modality-Agnostic Fusion for Multimodal Hidden Object Detection

Input-Time Scaling

Counterfactual Probabilistic Diffusion with Expert Models

Feedback-Driven Tool-Use Improvements in Large Language Models via Automated Build Environments

Bridging the Gap: A Framework for Real-World Video Deepfake Detection via Social Network Compression Emulation

Imposing AI: Deceptive design patterns against sustainability

LMAR: Language Model Augmented Retriever for Domain-specific Knowledge Indexing

Data-Driven Discovery of Mobility Periodicity for Understanding Urban Systems

Privacy Risks of LLM-Empowered Recommender Systems: An Inversion Attack Perspective

Web3 x AI Agents: Landscape, Integrations, and Foundational Challenges

Atherosclerosis through Hierarchical Explainable Neural Network Analysis

Survivability of Backdoor Attacks on Unconstrained Face Recognition Systems

Geological Everything Model 3D: A Promptable Foundation Model for Unified and Zero-Shot Subsurface Understanding

HiLight: A Hierarchical Reinforcement Learning Framework with Global Adversarial Guidance for Large-Scale Traffic Signal Control

AReaL: A Large-Scale Asynchronous Reinforcement Learning System for Language Reasoning

OMGM: Orchestrate Multiple Granularities and Modalities for Efficient Multimodal Retrieval

The Precautionary Principle and the Innovation Principle: Incompatible Guides for AI Innovation Governance?

A Framework for Testing and Adapting REST APIs as LLM Tools

D\'ej\`a Vu: Multilingual LLM Evaluation through the Lens of Machine Translation Evaluation

JARVIS-VLA: Post-Training Large-Scale Vision Language Models to Play Visual Games with Keyboards and Mouse

Prompt Programming: A Platform for Dialogue-based Computational Problem Solving with Generative AI Models

Auxiliary Discrminator Sequence Generative Adversarial Networks (ADSeqGAN) for Few Sample Molecule Generation

Neural Force Field: Few-shot Learning of Generalized Physical Reasoning

Towards Developing Socially Compliant Automated Vehicles: Advances, Expert Insights, and A Conceptual Framework

A Novel Approach to Balance Convenience and Nutrition in Meals With Long-Term Group Recommendations and Reasoning on Multimodal Recipes and its Implementation in BEACON

Can LLM Prompting Serve as a Proxy for Static Analysis in Vulnerability Detection

Tokens, the oft-overlooked appetizer: Large language models, the distributional hypothesis, and meaning

Polish-English medical knowledge transfer: A new benchmark and results

InterFormer: Effective Heterogeneous Interaction Learning for Click-Through Rate Prediction

AdvI2I: Adversarial Image Attack on Image-to-Image Diffusion models

A Survey on Group Fairness in Federated Learning: Challenges, Taxonomy of Solutions and Directions for Future Research

A Conflicts-free, Speed-lossless KAN-based Reinforcement Learning Decision System for Interactive Driving in Roundabouts

The Overcooked Generalisation Challenge: Evaluating Cooperation with Novel Partners in Unknown Environments Using Unsupervised Environment Design

Modelling the 5G Energy Consumption using Real-world Data: Energy Fingerprint is All You Need

Slaves to the Law of Large Numbers: An Asymptotic Equipartition Property for Perplexity in Generative Language Models

Interpretable Data-driven Anomaly Detection in Industrial Processes with ExIFFI

Analyzing the Impact of Adversarial Examples on Explainable Machine Learning

TSGCNeXt: Dynamic-Static Multi-Graph Convolution for Efficient Skeleton-Based Action Recognition with Long-term Learning Potential

Sufficient Invariant Learning for Distribution Shift

TORSO: Template-Oriented Reasoning Towards General Tasks

ForTIFAI: Fending Off Recursive Training Induced Failure for AI Models

Oyster-I: Beyond Refusal -- Constructive Safety Alignment for Responsible Language Models

Building Self-Evolving Agents via Experience-Driven Lifelong Learning: A Framework and Benchmark

QuantX: A Framework for Hardware-Aware Quantization of Generative AI Workloads

Learning to Plan with Personalized Preferences

Multi-Turn Human-LLM Interaction Through the Lens of a Two-Way Intelligibility Protocol

Spatio-Temporal Graphical Counterfactuals: An Overview

Standards in the Preparation of Biomedical Research Metadata: A Bridge2AI Perspective

Is In-Context Learning Learning?

Multimodal SAM-adapter for Semantic Segmentation

Diversified recommendations of cultural activities with personalized determinantal point processes

Improving Audio Event Recognition with Consistency Regularization

Data distribution impacts the performance and generalisability of contrastive learning-based foundation models of electrocardiograms

Towards Understanding Visual Grounding in Visual Language Models

GLAM: Geometry-Guided Local Alignment for Multi-View VLP in Mammography

I-Segmenter: Integer-Only Vision Transformer for Efficient Semantic Segmentation

Generalizing Beyond Suboptimality: Offline Reinforcement Learning Learns Effective Scheduling through Random Data

We Need a New Ethics for a World of AI Agents

SignClip: Leveraging Mouthing Cues for Sign Language Translation by Multimodal Contrastive Fusion

Openness in AI and downstream governance: A global value chain approach

SI-FACT: Mitigating Knowledge Conflict via Self-Improving Faithfulness-Aware Contrastive Tuning

Benchmark of stylistic variation in LLM-generated texts

BenchECG and xECG: a benchmark and baseline for ECG foundation models

Efficient Learning-Based Control of a Legged Robot in Lunar Gravity

Population-Aligned Persona Generation for LLM-based Social Simulation

Realism Control One-step Diffusion for Real-World Image Super-Resolution

Generating Energy-Efficient Code via Large-Language Models -- Where are we now?

Established Psychometric vs. Ecologically Valid Questionnaires: Rethinking Psychological Assessments in Large Language Models

Predictive Spike Timing Enables Distributed Shortest Path Computation in Spiking Neural Networks

TwinTac: A Wide-Range, Highly Sensitive Tactile Sensor with Real-to-Sim Digital Twin Sensor Model

Multimodal Mathematical Reasoning Embedded in Aerial Vehicle Imagery: Benchmarking, Analysis, and Exploration

Reinforcement learning for spin torque oscillator tasks

Exploring Expert Specialization through Unsupervised Training in Sparse Mixture of Experts

Intrinsic Dimension Estimating Autoencoder (IDEA) Using CancelOut Layer and a Projected Loss

Unsupervised Hallucination Detection by Inspecting Reasoning Processes

Drone-Based Multispectral Imaging and Deep Learning for Timely Detection of Branched Broomrape in Tomato Farms

Securing LLM-Generated Embedded Firmware through AI Agent-Driven Validation and Patching

Large Language Models Meet Legal Artificial Intelligence: A Survey

Limited Reference, Reliable Generation: A Two-Component Framework for Tabular Data Generation in Low-Data Regimes

Zero-Shot Referring Expression Comprehension via Visual-Language True/False Verification

Adaptive Token Merging for Efficient Transformer Semantic Communication at the Edge

SmartCoder-R1: Towards Secure and Explainable Smart Contract Generation with Security-Aware Group Relative Policy Optimization

WALL: A Web Application for Automated Quality Assurance using Large Language Models

An Autoencoder and Vision Transformer-based Interpretability Analysis of the Differences in Automated Staging of Second and Third Molars

Tackling One Health Risks: How Large Language Models are leveraged for Risk Negotiation and Consensus-building

Self-Augmented Robot Trajectory: Efficient Imitation Learning via Safe Self-augmentation with Demonstrator-annotated Precision

Automated Tuning for Diffusion Inverse Problem Solvers without Generative Prior Retraining

From Hugging Face to GitHub: Tracing License Drift in the Open-Source AI Ecosystem

Emulating Public Opinion: A Proof-of-Concept of AI-Generated Synthetic Survey Responses for the Chilean Case

Vibe Check: Understanding the Effects of LLM-Based Conversational Agents' Personality and Alignment on User Perceptions in Goal-Oriented Tasks

A Novel Approach to Balance Convenience and Nutrition in Meals With Long-Term Group Recommendations and Reasoning on Multimodal Recipes and its Implementation in BEACON

Created by

Haebom

저자

Vansh Nagpal, Siva Likitha Valluru, Kausik Lakkaraju, Nitin Gupta, Zach Abdulrahman, Andrew Davison, Biplav Srivastava

개요

본 논문은 건강한 사람과 건강 상태가 좋지 않은 사람 모두에게 중요한 식사 선택(아침, 점심, 저녁) 문제를 다룬다. 식사 선택은 영양(소금, 설탕 함량, 영양 성분)과 편의성(비용, 접근성, 요리 종류, 식재료) 간의 절충을 필요로 한다. 본 논문은 사용자의 선호도를 고려하면서 식품 구성 성분과 조리 과정을 고려한 데이터 기반 식사 추천 솔루션을 제시한다. 이 솔루션은 사용자 정의 가능한 식사 구성과 시간적 범위를 고려한다. 주요 기여는 '좋음(goodness)' 척도 도입, 텍스트 기반 레시피를 최근 도입된 다중 모드 풍부 레시피 표현(R3) 형식으로 변환하는 방법, 유망한 초기 결과를 보여주는 상황적 밴딧(contextual bandit) 학습 방법, 그리고 사용자 경험에 기반한 BEACON 시스템 프로토타입 개발이다.

시사점, 한계점

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시사점:

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사용자 맞춤형 식사 계획을 위한 데이터 기반 솔루션 제시.

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영양과 편의성을 모두 고려한 식사 추천 가능성 제시.

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텍스트 레시피를 R3 형식으로 변환하는 효율적인 방법 제시.

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상황적 밴딧 학습 방법을 통한 개인화된 식사 추천 성능 향상 가능성 제시.

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BEACON 시스템 프로토타입을 통해 실제 적용 가능성 확인.

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한계점:

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초기 결과만 제시되어 실제 적용 시 성능 및 효율성에 대한 추가적인 검증 필요.

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BEACON 시스템의 구체적인 성능 및 사용자 경험에 대한 자세한 분석 부족.

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다양한 사용자 그룹에 대한 일반화 가능성에 대한 추가 연구 필요.

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R3 형식 이외의 다른 레시피 표현 방식에 대한 고려 부족.

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